Swiss researchers have released a comprehensive dataset of residential electricity load profiles covering over 2,400 homes across 2023 and 2024. The dataset addresses a growing gap in real-world measurement data as residential consumption patterns shift dramatically due to widespread adoption of rooftop solar, heat pump heating systems, and electric vehicle charging.
The 15-minute resolution measurements capture both active and reactive power, including both energy withdrawal from and injection into the grid. This granularity is essential for accurate modeling of modern distribution networks where residential prosumers increasingly generate and consume power dynamically. The dataset covers diverse building types—apartments, single-family houses, and mixed-use installations—providing a representative cross-section of residential infrastructure.
A significant subset of participants took part in a pilot program testing innovative grid tariffs and automated load control strategies. This component adds unique value for researchers studying demand-side management and the potential of time-varying pricing to optimize grid operations. Metadata and tariff information are included alongside the measurements, enabling analysis of customer response to economic signals.
For the power industry, this dataset fills a critical research need. Distribution utilities and grid operators require accurate load profiles to design and operate networks supporting high penetration of rooftop generation and electrified heating and transportation. Inaccurate load forecasts at the distribution level can increase operational costs and compromise grid stability.
The availability of recent, high-resolution data from a developed European grid will enable advances in several areas: improved short-term and long-term load forecasting models, assessment of distribution system impacts from electrification, and evaluation of tariff designs that encourage flexible consumption. Researchers can also study how weather conditions, occupancy patterns, and appliance saturation influence consumption profiles in cold climates.
This open dataset represents a collaborative contribution to the energy transition research community, supporting the data-driven analysis necessary for reliable and efficient future grids.
